So the Analytics people has to be the one that simplifies the decision making process. They have to be the ones that help people consume the information in a way that is simple, not time consuming, not confusing and as univocal as possible. Analyzing and reporting are two completely different things, like I mentioned in “How to make self explaining reports“. But making the long story short, the person that analyzes the data goes through a process of questions and answers that generates the layers of information that will give context to the reported data (What I call the P.I.S.

In my book Meta Analytics I presented two sides of the analytics synapsis. The object that we analyze (companies) and the subject that make the analysis (the people). Between those two things there are a lot of things to deal with to convert the result of the synapsis in an insight that can be taken into action. In this post I’d like to talk about the object, the company. A company is a system, a set of parts that interact together with the common objective of adding value (in the present and in the future). So basically the information system

I remember that during the first wave of internet we tried to replicated the physical world but inside the browser. So buying cloths online was supposed to be like being in the store, which at that time was just impossible. It wasn’t until the second internet wave (after the crash of the first bubble) that we realized that internet won’t be or supposed to be like the real world. Actually it was able to be better but in a different way. During this second wave was where companies like Amazon came to make a revolution in the way we shop,

The idea of Meta Analytics (Beyond Analytics) is bringing up to the table a new way of understanding business, so we can measure them in a properly way facilitating a decision making process that brings companies closer to their business results. The current method for measuring performance is through KPIs or Key performance indicators. KPIs were helping us measuring our companies’ performance almost for ever and the feeling was always (at least in my case) that they accomplish that goal when measuring the performance of areas or departments but not when measuring the company’s performance as a whole. The Meta

We can say a lot of things about internet, but can’t say that is not responsible for making regular civilians a little geeks. After internet, no matter your age, sex, or profession, people is involved in technology. If you work in marketing, you know about technology, if you work in finance you know about technology, if you work in logistics, you know about technology. The problem is that, as you can imagine, not all of us are experts in everything, and that’s alright. The problem is that at some point it seems that we don’t know exactly what we don’t

The digital revolution has begun to show us its results, and the winner is… It’s incredible how everything had changed since I started writing this blog more than a decade ago and is not because the human is bringing some new behavior to the table, as a matter of fact there’s nothing new (really new) under the sun. It’s just basically that everything that we use to do in analogical way is getting digital, and it’s not just “a different way”. It’s actually way more than that, probably like a revolution and like in any other revolution there are winners

This is the list of top 10 Fortune companies: Walmart: Founded in 1962. Berkshire Hathaway: Founded in 1839. Apple: Founded in 1976. Exxon mobile: Founded in 1870. McKesson: Founded in 1833. United Health Group: Founded in 1977. CVS Health: Founded in 1963. General Motors: Founded in 1908. AT&T: Founded in 1983. Ford Motors: Founded in 1903. Information was historically expensive until the following products were lunched. Google Analytics: Was launched in 2005. It was after 2009 that it added features to convert the platform into a Corporative Solution. Amazon Web Services: Launched in 20016. Apache Hadoop: Launched in 2011. Google

Whether you are an experience analytics professional, or you are just making your first steps in Analytics these are six habits that will definitely improve your performance. Planning vs implementation time distribution: The digital industry is definitely pragmatic and due its dynamism there’s normally no time for anything. However a common mistake is going from the idea to the implementation with no, or not enough planning. If I would have to put a number, I would say that it has to be 80% planning and 20% implementation. But why almost nobody invest 80% in planning and research? Because during planning

It’s been seven years since Meta Analytics was published. In that book instead of focusing on the technical aspects I wrote mainly about two main pillars on the insights process. 1) The object: The object is what the subject (the person) will analyze. Understanding the “substance” of what we are analyzing is key to generate a proper interpretation of what is been observe. The object in our case are companies. Companies are systems, a set of things that interact together with a common objective which is making money today (ie Ebitda) and in the future (ie Purchasing intention). The parts

Well, remember that in my past post I was talking about trusting your main source of value to a third party that can have a different objective/s than yours? I also mentioned the example of using Google Attribution Model. Well, if I would be Google I would try with all my might to be the one that sets the standard of the attribution model the people use. Why? Because the attribution model is the one that tells you how and where you should invest your advertising budget. So, apparently Google is aligned with that idea, because has just launched their “free Google Attribution” model.